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Examination (HINE). However, current predictive models lack integration of these modalities and precision in individualized diagnosis and prognosis. As part of the ENSEMBLE Project—a multinational study funded
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individualized diagnosis and prognosis. As part of the ENSEMBLE Project—a multinational study funded by the Fondation Paralysie Cérébrale—you will help develop a machine learning-based multimodal prediction tool
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(BHMs) to infer the fundamental parameters of large stellar populations and their hosted planets in a statistically self-consistent way. By jointly modelling ensembles of stars and incorporating high
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that are transforming many sectors today through language models, recommendation systems and advanced technologies. However, modern machine learning models, such as neural networks and ensemble models, remain largely
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networks, ensemble algorithms, and other advanced architectures, the objective will be to accurately predict the state of health (SoH) of batteries in the short, medium, and long term, including under
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Characterisation Apply and refine ML techniques for in silico annotation, prediction of physicochemical properties, and prioritisation of chemicals by toxicity or biological relevance. Integrative Analysis of Large
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comparative, ainsi qu'à un ensemble innovant de deux jeux de données correspondant à une plante domestique (le maïs) et à son ancêtre sauvage (la téosinte). La comparaison entre les deux espèces permettra
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starting: Develop multiphysics models for the complete supply chain of selected heat-sensitive biological products. This includes hygrothermal transport in the ensemble of packed products during cooling